A decision tree is a structure that resembles a flowchart in its functioning. Decision trees are vital in the field of Machine Learning as they are used in the process of predictive modeling. The structures are built by using algorithms that split up the input data based on a variety of conditions. Decision trees are used for supervised learning in both classification and regression methodologies. Based on the method chosen, they're called either classification trees or regression trees. The entire goal of using a decision tree is to build a model that can predict the value of a target variable based on the decision rules that can be inferred from the features. One thing to note is that the deeper the tree is, the more complex the rules are.
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